We have developed methods for automated detection of cultural monuments and sites that are concealed by outfields and forestlands. <\/strong><\/p>\n\n\n\n The current mapping of cultural heritage sites in forests and outfields is incomplete and inaccurate. This can lead to the potential loss or damage of valuable sites and monuments during development projects. In collaboration with the Directorate of Cultural Heritage in Norway and selected county administrations, we have developed automated detection methods to locate previously unmapped cultural heritage sites using laser scanning and deep learning. Airborne laser scanning enables us to assess ground levels, and makes it easier to detect sites of significance. <\/p>\n\n\n\n After testing a few different approaches with varying success, including template matching and a deep convolutional neural network (CNN), we landed on our current method, which leverages the power of Faster R-CNN. This deep neural network was pretrained on one million natural scene images that featured labelled objects such as vehicles, animals and people. This endowed the network with basic object detection capabilities which was then fine-tuned with laser scanning images that featured 3.000 known instances of various cultural heritage sites. Our advanced approach could then be used to accurately predict the locations of grave mounds, pitfall traps and charcoal kilns, even when they were not part of the training dataset. <\/p>\n\n\n\n The true value of an automated prediction is to detect unknown locations. To test our method, we chose \u00d8vre Eiker municipality which, at that point, only had about ten previously known charcoal kiln locations. Given its proximity to Kongberg’s silver mines, which used charcoal in the 1600s, we therefore suspected many more sites. Our method covered the entire municipality and predicted 1.130 locations. Upon manual inspection, 578 (51%) were confirmed, and we found an additional 66 charcoal kilns that the automated method had missed. <\/p>\n\n\n\n During the project period, we made several other notable discoveries. These included identifying iron extraction sites and pitfall traps for deer in \u00d8ystre Slidre, as well as detecting sixteen burial mounds in the country municipalities of Vestfold and Telemark.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n<\/div>\n\n\n\n![\"The](\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2023\/11\/Charcoal-kiln-cropped-1024x562.jpg\")
Deep learning for cultural heritage management<\/h2>\n\n\n\n
![\"The](\"https:\/\/nr.no\/content\/uploads\/sites\/2\/2023\/11\/laserscanning-culturalheriage.jpg\")
Mapping charcoal kilns, iron extraction sites and burial mounds<\/h2>\n\n\n\n
To learn more about this project, please contact:<\/h3>\n\n\n\t\t
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